As the demand on the food supply increases and the total viable farmland decreases, methods and systems are needed that maximize crop yields. Maximum crop yields result in increased production of agricultural products and more value per acre of land. However, the effort in maximizing crop yields is difficult, time consuming, and costly in part because the characteristics of farmland vary from acre to acre. This variance is due to factors such as the conditions of the soil and topography. Further, an agricultural farm field may include significant acre-to-acre variations in nutrients, quality of crop produced, and ultimately crop yield.
The current practice is to prescribe agricultural inputs, such as seed and fertilizer, to the entire agricultural farm field according to the needs of the most deficient soil, or according to the averaged requirements of the different soils. The result is that a substantial area of the field can receive either more or less of the item being applied than what the site specific areas can efficiently use to produce agronomic output, resulting in either a significant waste of expensive ag inputs or unrealized yield potential.
Growers and their agronomic advisors can make more accurate input decisions with access to more accurate data of site specific agronomic responses. Agronomic decision making has been driven by a research model that involves yield and other observations from small plots with various treatments. Examples would be yield by applied nitrogen rates or seeding rate. Such testing suffers from the limitation of being able to translate the results observed in a small plot at a research farm to production fields, which typically have different background conditions of soils, fertility, management practices, etc.
It would be desirable to develop a system and method to randomize and replicate agronomic inputs within different management zones of a field to measure the agronomic response to an input within several different contexts: i) management zone specific, ii) region specific and iii) growing season weather specific.